Computationally Modelling Cholesterol Metabolism and Atherosclerosis

Abstract

Cardiovascular disease (CVD) is the leading cause of death globally. The underlying pathological driver of CVD is atherosclerosis. The primary risk factor for atherosclerosis is elevated low-density lipoprotein cholesterol (LDL-C). Dysregulation of cholesterol metabolism is synonymous with a rise in LDL-C. Due to the complexity of cholesterol metabolism and atherosclerosis mathematical models are routinely used to explore their non-trivial dynamics. Mathematical modelling has generated a wealth of useful biological insights, which have deepened our understanding of these processes. To date however, no model has been developed which fully captures how whole-body cholesterol metabolism intersects with atherosclerosis. The main reason for this is one of scale. Whole body cholesterol metabolism is defined by macroscale physiological processes, while atherosclerosis operates mainly at a microscale. This work describes how a model of cholesterol metabolism was combined with a model of atherosclerotic plaque formation. This new model is capable of reproducing the output from its parent models. Using the new model, we demonstrate how this system can be utilized to identify interventions that lower LDL-C and abrogate plaque formation.

Keywords: atherosclerosis; cardiovascular disease (CVD); cholesterol; low density lipoprotein cholesterol (LDL-C); mathematical model; plaque.

Figure 1

SBGN diagram of the Gomez-Cabrero et al. (2011) [72] model of atherogenesis.

Figure 2

Combined SBGN network diagram of whole-body cholesterol metabolism and its intersection with atherosclerosis. Adapted from [56,72].

Figure 3

Parameter scan results of (a) M on LDL, HDL, plaque size and oxLDL and (b) M and DC in tandem on plaque size. For (a), the solid black line () represents LDL, the square dot line () signifies HDL, the long dash line () is representative of plaque size, and the long dash dot line () characterises oxLDL.

Figure 4

Comparison of results from the merged model with (a) Gomez-Cabrero et al. (2011) [72] and (b) Mc Auley et al. (2012) [56]. In (a), the grey solid line () represents plaque size in the merged model and the grey dashed line () characterises plaque size in the Gomez-Cabrero et al. (2011) [72] model (left y-axis). The black solid line () represents LDL in the merged model and the black dashed line () signifies LDL in the Gomez-Cabrero et al. (2011) [72] model (right y-axis). In (b), the light grey solid line () is representative of LDLC in the merged model, the round dot line () represents LDLC in the Mc Auley et al. (2012) [56] model, and the square dot line () signifies LDLC in the Mc Auley et al. (2012) [56] model when DC was adjusted to 1051 mg/day. The dark grey line () describes HDLC in the merged model, the dashed line () represents HDLC in the Mc Auley et al. (2012) [56] model, and the dash dot line () is representative of HDLC in the Mc Auley et al. (2012) [56] model when 1051 mg/day of cholesterol ingestion was simulated.

Figure 5

Impact of statin, sterol and combination therapy on (a) LDLC and (b) plaque size, and the impact of statin, sterol and combination therapy, dependent on DC, on (c) LDLC and (d) plaque size. Solid lines () represent baseline values; square dot lines () signify statin treatment; dashed lines () represent sterol treatment; and long dash dot lines () characterise combination therapy.